Journal of Computer-Aided Molecular Design

, Volume 23, Issue 8, pp 527–539 | Cite as

Virtual fragment screening: an exploration of various docking and scoring protocols for fragments using Glide

  • Sameer Kawatkar
  • Hongming Wang
  • Ryszard Czerminski
  • Diane Joseph-McCarthyEmail author


Fragment-based drug discovery approaches allow for a greater coverage of chemical space and generally produce high efficiency ligands. As such, virtual and experimental fragment screening are increasingly being coupled in an effort to identify new leads for specific therapeutic targets. Fragment docking is employed to create target-focussed subset of compounds for testing along side generic fragment libraries. The utility of the program Glide with various scoring schemes for fragment docking is discussed. Fragment docking results for two test cases, prostaglandin D2 synthase and DNA ligase, are presented and compared to experimental screening data. Self-docking, cross-docking, and enrichment studies are performed. For the enrichment runs, experimental data exists indicating that the docking decoys in fact do not inhibit the corresponding enzyme being examined. Results indicate that even for difficult test cases fragment docking can yield enrichments significantly better than random.


Virtual screening Structure-based drug design Enrichment rate Fragment libraries Prostaglandin D synthase DNA ligase 



We thank Joann Prescott-Roy, Rutger Folmer, Loredana Spadola, and Peter Kenny for their help in locating and curating data sets and Adam Shapiro for providing experimental data on ligase in advance of publication.

Supplementary material

10822_2009_9281_MOESM1_ESM.pdf (53 kb)
PDF 53 kb


  1. 1.
    Howard S, Berdini V, Boulstridge JA, Carr MG, Cross DM, Curry J, Devine LA, Early TR, Fazal L, Gill AL, Heathcote M, Maman S, Matthews JE, McMenamin RL, Navarro EF, O’Brien MA, O’Reilly M, Rees DC, Reule M, Tisi D, Williams G, Vinkovic M, Wyatt PG (2009) Fragment-based discovery of the pyrazol-4-yl urea (AT9283), a multitargeted kinase inhibitor with potent aurora kinase activity. J Med Chem 52:379–388. doi: 10.1021/jm800984v CrossRefGoogle Scholar
  2. 2.
    Edwards PD, Albert JS, Sylvester M, Aharony D, Andisik D, Callaghan O, Campbell JB, Carr RA, Chessari G, Congreve M, Frederickson M, Folmer RH, Geschwindner S, Koether G, Kolmodin K, Krumrine J, Mauger RC, Murray CW, Olsson LL, Patel S, Spear N, Tian G (2007) Application of fragment-based lead generation to the discovery of novel, cyclic amidine beta-secretase inhibitors with nanomolar potency, cellular activity, and high ligand efficiency. J Med Chem 50:5912–5925. doi: 10.1021/jm070829p CrossRefGoogle Scholar
  3. 3.
    Geschwindner S, Olsson LL, Albert JS, Deinum J, Edwards PD, de Beer T, Folmer RH (2007) Discovery of a novel warhead against beta-secretase through fragment-based lead generation. J Med Chem 50:5903–5911. doi: 10.1021/jm070825k CrossRefGoogle Scholar
  4. 4.
    Albert JS, Blomberg N, Breeze AL, Brown AJ, Burrows JN, Edwards PD, Folmer RH, Geschwindner S, Griffen EJ, Kenny PW, Nowak T, Olsson LL, Sanganee H, Shapiro AB (2007) An integrated approach to fragment-based lead generation: philosophy, strategy and case studies from AstraZeneca’s drug discovery programmes. Curr Top Med Chem 7:1600–1629. doi: 10.2174/156802607782341091 CrossRefGoogle Scholar
  5. 5.
    Erlanson DA, Wells JA, Braisted AC (2004) Tethering: fragment-based drug discovery. Annu Rev Biophys Biomol Struct 33:199–223. doi: 10.1146/annurev.biophys.33.110502.140409 CrossRefGoogle Scholar
  6. 6.
    Hohwy M, Spadola L, Lundquist B, Hawtin P, Dahmen J, Groth-Clausen I, Nilsson E, Persdotter S, von Wachenfeldt K, Folmer RH, Edman K (2008) Novel prostaglandin D synthase inhibitors generated by fragment-based drug design. J Med Chem 51:2178–2186. doi: 10.1021/jm701509k CrossRefGoogle Scholar
  7. 7.
    Payne DJ, Gwynn MN, Holmes DJ, Pompliano DL (2007) Drugs for bad bugs: confronting the challenges of antibacterial discovery. Nat Rev Drug Discov 6:29–40. doi: 10.1038/nrd2201 CrossRefGoogle Scholar
  8. 8.
    Hopkins AL, Groom CR, Alex A (2004) Ligand efficiency: a useful metric for lead selection. Drug Discov Today 9:430–431. doi: 10.1016/S1359-6446(04)03069-7 CrossRefGoogle Scholar
  9. 9.
    Kuntz ID, Chen K, Sharp KA, Kollman PA (1999) The maximal affinity of ligands. Proc Natl Acad Sci USA 96:9997–10002. doi: 10.1073/pnas.96.18.9997 CrossRefGoogle Scholar
  10. 10.
    Abad-Zapatero C, Metz JT (2005) Ligand efficiency indices as guideposts for drug discovery. Drug Discov Today 10:464–469. doi: 10.1016/S1359-6446(05)03386-6 CrossRefGoogle Scholar
  11. 11.
    Carr RAE, Congreve M, Murray CW, Rees DC (2005) Fragment-based lead discovery: leads by design. Drug Discov Today 10:987–992. doi: 10.1016/S1359-6446(05)03511-7 CrossRefGoogle Scholar
  12. 12.
    Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (1997) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 23:3–25. doi: 10.1016/S0169-409X(96)00423-1 CrossRefGoogle Scholar
  13. 13.
    Oprea TI (2000) Property distribution of drug-related chemical databases. J Comput Aided Mol Des 14:251–264. doi: 10.1023/A:1008130001697 CrossRefGoogle Scholar
  14. 14.
    Oprea TI, Davis AM, Teague SJ, Leeson PD (2001) Is there a difference between leads and drugs? A historical perspective. J Chem Inf Comput Sci 41:1308–1315. doi: 10.1021/ci010366a Google Scholar
  15. 15.
    Veber DF, Johnson SR, Cheng H-Y, Smith BR, Ward KW, Kopple KD (2002) Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem 45:2615–2623. doi: 10.1021/jm020017n CrossRefGoogle Scholar
  16. 16.
    Congreve M, Carr R, Murray C, Jhoti H (2003) A ‘rule of three’ for fragment-based lead discovery? Drug Discov Today 8:876–877. doi: 10.1016/S1359-6446(03)02831-9 CrossRefGoogle Scholar
  17. 17.
    Joseph-McCarthy D, Baber JC, Feyfant E, Thompson DC, Humblet C (2007) Lead optimization via high-throughput molecular docking. Curr Opin Drug Discov Dev 10:264–274Google Scholar
  18. 18.
    Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, Repasky MP, Knoll EH, Shelley M, Perry JK, Shaw DE, Francis P, Shenkin PS (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47:1739–1749. doi: 10.1021/jm0306430 CrossRefGoogle Scholar
  19. 19.
    Halgren TA, Murphy RB, Friesner RA, Beard HS, Frye LL, Pollard WT, Banks JL (2004) Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. J Med Chem 47:1750–1759. doi: 10.1021/jm030644s CrossRefGoogle Scholar
  20. 20.
    Friesner RA, Murphy RB, Repasky MP, Frye LL, Greenwood JR, Halgren TA, Sanschagrin PC, Mainz DT (2006) Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein–ligand complexes. J Med Chem 49:6177–6196. doi: 10.1021/jm051256o CrossRefGoogle Scholar
  21. 21.
    Hohwy M, Spadola L, Lundquist B, Hawtin P, Dahmén J, Groth-Clausen I, Nilsson E, Persdotter S, von Wachenfeldt K, Folmer R, Edman K (2008) Novel prostaglandin D synthase inhibitors generated by fragment-based drug design. J Med Chem 51:2178–2186. doi: 10.1021/jm701509k CrossRefGoogle Scholar
  22. 22.
    Aritake K, Kado Y, Inoue T, Miyano M, Urade Y (2006) Structural and functional characterization of HQL-79, an orally selective inhibitor of human hematopoietic prostaglandin D synthase. J Biol Chem 281:15277–15286. doi: 10.1074/jbc.M506431200 CrossRefGoogle Scholar
  23. 23.
    Engler MJ, Richardson CC (1982) DNA ligases. In: Boyer PD (ed) The enzymes. Academic Press, Inc., New York, NY, pp 3–29Google Scholar
  24. 24.
    Kenny PW (2009) J Comput Aided Mol Des In (this issue)Google Scholar
  25. 25.
    Weininger D (1988) SMILES 1. Introduction and encoding rules. J Chem Inf Comput 28:31–36Google Scholar
  26. 26.
    Kenny PW, Sadowski J (2004) Structure modification in chemical databases. In: Opera TI (ed) Chemoinformatics in drug discovery. Wiley, Weinheim, pp 271–285Google Scholar
  27. 27.
    Lyne PD, Lamb ML, Saeh JC (2006) Accurate prediction of the relative potencies of members of a series of kinase inhibitors using molecular docking and MM-GBSA scoring. J Med Chem 49:4805–4808. doi: 10.1021/jm060522a CrossRefGoogle Scholar
  28. 28.
    Chen HM, Lyne PD, Giordanetto F, Lovell T, Li J (2006) Evaluating molecular-docking methods for pose prediction and enrichment factors. J Chem Inf Model 46:401–415. doi: 10.1021/ci0503255 CrossRefGoogle Scholar
  29. 29.
    Triballeau N, Acher F, Brabet I, Pin JP, Bertrand HO (2005) Virtual screening workflow development guided by the “receiver operating characteristic” curve approach. Application to high-throughput docking on metabotropic glutamate receptor subtype 4. J Med Chem 48:2534–2547. doi: 10.1021/jm049092j CrossRefGoogle Scholar
  30. 30.
    Sing T, Sander O, Beerenwinkel N, Lengauer T (2005) ROCR: visualizing classifier performance in R. Bioinformatics 21:3940–3941. doi: 10.1093/bioinformatics/bti623 CrossRefGoogle Scholar
  31. 31.
    Sherman W, Day T, Jacobson MP, Friesner RA, Farid R (2006) Novel procedure for modeling ligand/receptor induced fit effects. J Med Chem 49:534–553. doi: 10.1021/jm050540c CrossRefGoogle Scholar
  32. 32.
    Verdonk ML, Mortenson PN, Hall RJ, Hartshorn MJ, Murray CW (2008) Protein-ligand docking against non-native protein conformers. J Chem Inf Model 48:2214–2225. doi: 10.1021/ci8002254 CrossRefGoogle Scholar
  33. 33.
    Graves AP, Shivakumar DM, Boyce SE, Jacobson MP, Case DA, Shoichet BK (2008) Rescoring docking hit lists for model cavity sites: predictions and experimental testing. J Mol Biol 377:914–934. doi: 10.1016/j.jmb.2008.01.049 CrossRefGoogle Scholar
  34. 34.
    Thompson DC, Humblet C, Joseph-McCarthy D (2008) Investigation of MM-PBSA rescoring of docking poses. J Chem Inf Model 48:1081–1091. doi: 10.1021/ci700470c CrossRefGoogle Scholar
  35. 35.
    Cummings MD, DesJarlais RL, Gibbs AC, Mohan V, Jaeger EP (2005) Comparison of automated docking programs as virtual screening tools. J Med Chem 48:962–976. doi: 10.1021/jm049798d CrossRefGoogle Scholar
  36. 36.
    Warren GL, Andrews CW, Capelli AM, Clarke B, LaLonde J, Lambert MH, Lindvall M, Nevins N, Semus SF, Senger S, Tedesco G, Wall ID, Woolven JM, Peishoff CE, Head MS (2006) A critical assessment of docking programs and scoring functions. J Med Chem 49:5912–5931. doi: 10.1021/jm050362n CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Sameer Kawatkar
    • 1
  • Hongming Wang
    • 1
  • Ryszard Czerminski
    • 1
  • Diane Joseph-McCarthy
    • 1
    Email author
  1. 1.AstraZeneca, R&D BostonWalthamUSA

Personalised recommendations